CHATREPORT: Democratizing Sustainability Disclosure Analysis through LLM-based Tools
Jingwei Ni, Julia Bingler, Chiara Colesanti-Senni, Mathias Kraus, Glen, Gostlow, Tobias Schimanski, Dominik Stammbach, Saeid Ashraf Vaghefi, Qian, Wang, Nicolas Webersinke, Tobias Wekhof, Tingyu Yu, Markus Leippold

TL;DR
ChatReport introduces an LLM-based system that automates sustainability report analysis, making it more accessible and transparent by addressing hallucination issues and involving domain experts, with publicly available datasets and analyses.
Contribution
The paper presents a novel LLM-based tool for analyzing sustainability reports, incorporating traceability and expert involvement to improve accuracy and transparency.
Findings
Analyzed 1015 reports with the system
Made datasets and analyses publicly available
Reduced hallucination effects in LLM outputs
Abstract
In the face of climate change, are companies really taking substantial steps toward more sustainable operations? A comprehensive answer lies in the dense, information-rich landscape of corporate sustainability reports. However, the sheer volume and complexity of these reports make human analysis very costly. Therefore, only a few entities worldwide have the resources to analyze these reports at scale, which leads to a lack of transparency in sustainability reporting. Empowering stakeholders with LLM-based automatic analysis tools can be a promising way to democratize sustainability report analysis. However, developing such tools is challenging due to (1) the hallucination of LLMs and (2) the inefficiency of bringing domain experts into the AI development loop. In this paper, we ChatReport, a novel LLM-based system to automate the analysis of corporate sustainability reports, addressing…
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Taxonomy
TopicsBig Data and Business Intelligence · Corporate Social Responsibility Reporting · Information and Cyber Security
